日本産キンラン属における菌従属性に関する進化学的研究

要約のみTohoku University牧雅之課

Linear Ballistic Accumulator Modeling of Attentional Bias Modification Revealed Disturbed Evidence Accumulation of Negative Information by Explicit Instruction

In recent years, several attentional bias modification (ABM) studies have been conducted. Previous studies have suggested that explicit instruction (i.e., informing participants of the contingency of stimuli) enhances the effect of ABM. However, the specific working mechanism has not been identified. This is partly because reaction time (RT) data are typically reduced to an attention bias score, which is a mere difference of RT between experimental and control conditions. This data reduction causes a loss of information, as RT reflects various cognitive processes at play while making a response or decision. To overcome this issue, the present study applied linear ballistic accumulator (LBA) modeling to the outcomes (RT measures) of explicitly guided (compared to standard) ABM. This computational modeling approach allowed us to dissociate RTs into distinct components that can be relevant for attentional bias, such as efficiency of information processing or prior knowledge of the task;this provides an understanding of the mechanism of action underlying explicitly guided ABM. The analyzed data were RT-observed in the dot-probe task, which was administered before and after 3-days of ABM training. Our main focus was on the changes in LBA components that would be induced by the training. Additionally, we analyzed in-session performances over the 3 days of training. The LBA analysis revealed a significant reduction in processing efficiency (i.e., drift rate) in the congruent condition, where the target probe is presented in the same location as a negative stimulus. This explains the reduction in the overall attentional bias score, suggesting that explicit ABM suppresses processing of negative stimuli. Moreover, the results suggest that explicitly guided ABM may influence prior knowledge of the target location in the training task and make participants prepared to respond to the task. These findings highlight the usefulness of LBA-based analysis to explore the underlying cognitive mechanisms in ABM, and indeed our analyses revealed the differences between the explicit and the standard ABM that could not be identified by traditional RT analysis or attentional bias scores

Layout Optimization of the Beam Spot Locations Scanned by Electromagnets in Particle Beam Therapy

This paper presents a layout optimization method of the spot locations of pencil beam scanning for particle beam cancer therapy. With the pencil beam scanning technique, the particle beam is scanned from spot to spot in the tumor by using scanning magnets. To provide clinically ideal dose distributions and less-invasive treatment to the patients, both the spot locations and the number of particles given to each spot should be optimized. However, the spot layout is fixed with a lattice pattern in many prior studies. We propose the optimization method to derive the non-lattice spot layout to realize an acceptable dose distribution with a reduced number of spots. With the proposed method, a large enough number of spots were located densely at the initial state, and then the spots with the smallest contribution were removed one by one through iterations. The number of particles given to each spot was determined by solving a quadratic problem. Furthermore, we also propose the idea to accelerate the optimization process by simultaneously removing multiple spots. The algorithm was confirmed by numerical examples of both two-dimensional and three-dimensional cases. The dose quality with the optimized spot layout was better than that with the conventional lattice spot patterns, with all tested cases. In the optimized spot layout, the spots were located on the closed lines which were concentric to the target contour. We also confirmed the proposed method of multiple-remotion can accelerate the optimization process without violating the dose quality

Increased vesicle fusion competence underlies long-term potentiation at hippocampal mossy fiber synapses

Presynaptic long-term potentiation (LTP) is thought to play an important role in learning and memory. However, the underlying mechanism remains elusive because of the difficulty of direct recording during LTP. Hippocampal mossy fiber synapses exhibit pronounced LTP of transmitter release after tetanic stimulation and have been used as a model of presynaptic LTP. Here, we induced LTP by optogenetic tools and applied direct presynaptic patch-clamp recordings. The action potential waveform and evoked presynaptic Ca2+ currents remained unchanged after LTP induction. Membrane capacitance measurements suggested higher release probability of synaptic vesicles without changing the number of release-ready vesicles after LTP induction. Synaptic vesicle replenishment was also enhanced. Furthermore, stimulated emission depletion microscopy suggested an increase in the numbers of Munc13-1 and RIM1 molecules within active zones. We propose that dynamic changes in the active zone components may be relevant for the increased fusion competence and synaptic vesicle replenishment during LTP